Triple
T454837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Unity Day |
E7210
|
entity |
| Predicate | flagUsage |
P2529
|
FINISHED |
| Object | federal flag flown on public buildings |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: federal flag flown on public buildings | Statement: [German Unity Day, flagUsage, federal flag flown on public buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flagUsage Context triple: [German Unity Day, flagUsage, federal flag flown on public buildings]
-
A.
flagDescription
Indicates that a textual explanation or label is provided describing the meaning, purpose, or status represented by a particular flag.
-
B.
flag
Indicates that one entity marks, signals, or draws attention to another entity, often to denote status, importance, or the need for review or action.
-
C.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
D.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
E.
flagshipFor
Indicates that one entity serves as the primary or leading representative example for another entity, often embodying its most important qualities or status.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef87cc7c8190a0fec933457821e2 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede4de008190b5a6c159e741522e |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.